In various location-based services (LBS) technologies, the detection of the position, type, width, color, and quantity of lane lines is of great significance to autonomous or aided driving, map navigation, and generation of basic geographic data.
An existing lane line detection method generally includes the following process: performing edge detection on an original image, binarizing the edge detection result, extracting a lane line by performing a Hough transform or a random Hough transform on the binarizing result or by using a ransac algorithm, and finally performing fine processing on the extracted lane line. Such a method has a high lane line identification accuracy for clear images when the lane line is not blocked by other objects. However, once the edge of the lane line in the image is not clear or the lane line is blocked by other objects, the detection accuracy of the existing detection method is not satisfactory.